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Could 4G help rural areas get online?

While the government likes to talk about broadband as a commodity, alongside water or electricity, the sad truth is that many rural areas can get little to no service. There have been many false dawns in rural broadband; so is 4G set to be the next one, or is it the real deal?

In simple terms, 4G mobile broadband is set to slowly replace the current 3G networks we have cross the UK. You’ll need a new smartphone or dongle to access it, but otherwise it should smoothly replace 3G while offering the promise of faster, more reliable mobile data transfer.

The case for 4G mobile broadband

The 4G revolution certainly has the potential to meet rural needs. Rollout should be relatively straightforward, with first-to-market EE (Orange and T-Mobile) having already brought 4G to 27 UK towns and cities since launching late in 2012.

Price shouldn’t be an issue either. Mobile network Three has announced it will not charge a premium (above its 3G charges) for 4G mobile broadband, so it will be tough for the other networks to do so once competition for customers hots up.

Then there are the speeds. EE has been quoting averages from 8-12Mb since launch, with the current potential for 40Mb max speeds. While this is a long way behind current UK fixed-line speeds over fibre (which are already 100Mb and rising), 40Mb would be more than fast enough for the majority of rural customers’ needs.

And better still, this is potentially the tip of the iceberg in terms of speed. Etislat tests last year clocked a new 4G record at more than 300Mb and while you’re not likely to get that in a windy field near you anytime soon, it shows what this fledgling technology still in the locker.

The case against

As always tends to be the case when it comes to broadband, the biggest barrier to rural 4G is money. While the mobile internet providers are always quick to get their shiny new networks up and running in London, Birmingham and Manchester, those of us living in less population dense areas know the postcode lottery all too well. The talk is always of ‘population’ coverage, not geographical, and you can be sure the 4G rollout will be no different.

Then there’s reliability. We’ve had 3G for a long time now and enjoy very high UK coverage in terms of population, but standing stock still isn’t often enough to hold a reliable signal – let alone moving around. This can make data downloads a tedious task, while streaming can be next to useless. When 3G arrived there was much talk of being able to scrap your fixed line connection – something few have gone on to risk.

This leads us nicely onto speeds. Again, while first 7Mb and then 14Mb were promised the UK average 3G mobile broadband speed has never really got higher than 1-2Mb. Independent 4G field testing isn’t averaging out at 10Mb yet, so for now the jury is very much out. However, many a rural broadband customer would happily accept a reliable 10Mb broadband package.

So yes, 4G mobile broadband has the potential to get rural areas online. But unless you have a very active council or business community getting behind your push for base stations, I wouldn’t start holding your breath just yet.

Author Bio: Matt Powell is the editor for the broadband provider comparison site Broadband Genie.

Get in the back! The robot’s driving.

The much vaunted phenomenon of automated cars has returned again to the news this week, Read this here. Events like the DARPA Grand Challenge and their ilk continue however to demonstrate that robots can and probably will develop into the way forward for general purpose motoring and transportation.

The storms in Scotland yesterday saw enormous numbers of vehicles struggling to cope with the adverse conditions and either blowing over or bashing into each other and it probably wont be the last time the winter weather presents challenges to the UK motorist with snow gently falling over our Ayrshire offices again this morning.

These two events show the stark contrast between human and robotic drivers. The simple fact is, well before the end of the next decade, humans will be relegated from the drivers seat into the passenger seats. Ok perhaps not all vehicles will conform to this model. Some vehicles will still allow a human to sit behind the wheel, but only with a vigilant robot “supervisor” who will watch their every move and silently fix the human mistakes whilst simoultaneously scanning for unforeseen hazards. Driving a car as we do today will become a risky hobby which will only be possible on specially designed closed courses.

You think this sounds far fetched? Its no less far fetched however than the notion that humans could be trusted behind the wheel of a vehicle in the first place. Henry Ford would look at todays vehicles with incredulity if he did so in the context of the annual death toll on our UK roads which stood at over 2000 last year. The simple fact is we are terrible drivers and getting steadily worse as technology inside and outside vehicles demands more and more from us. The modern car is probably comparable in complexity of systems to a fighter jet of only a few decades ago.

Couple this with the fact that we are often just plain stupid, our eyesight is poor, our hearing suspect even if we choose not to be blasting the latest hits on our car stereos and we lack any appreciation at all of Newtonian physics, blindly tailgating at 80mph in rush hour traffic. Theres no escaping the fact that judgment is evident on the roads only by its absence. In stark contrast, robot drivers can be programmed with the most vulcan style logic coupled with sensory powers that put the human driver to shame.

The robots in the DARPA Grand Challenge could be easily programmed with the full highway code and could sense distances to within a millimetre in the daylight, in fog or even in the dark They could see in the dark and through the sort of fog that would blind any human driver. These robots are but the first members of a class of devices that will advance along a steep curve like that traced by computers and the Internet over the last two decades and will ultimately seem as old hat as a Sinclair ZX Spectrum in a few short years.

Its important however to bear in mind that filling the UK’s roads with robot controlled vehicles is about much more than road safety. The introduction of such capable vehicle control could enable the virtual elimination of traffic congestion by safely increasing the density of vehicles per mile by an order of magnitude. They could also eliminate the need for traffic lights, by having robot controlled vehicles safely nip through the gaps in the crossflow traffic rather than waste time waiting for green lights.

Robotic vehicles could also turn commutes into productive time enabling the human passengers to sit back and catch up on work, watch TV, access the net or even sleep. Indeed it would no longer be a necessity to be able to drive in the first place to make use of the road traffic networks enabling the very young or the very old to get from A to B. Imagine no more school runs or newly qualified driver deaths due to inexperience or worse. One thing is certain though. This prediction will seem ever so quaint in a few years as the whole model of how we move around will be rewritten in ways we cannot yet imagine by the introduction of automated transport. The advent of automated transport is as profound a change as the arrival of the horseless carriage 100 or more years ago and the impact on global society today is no less unpredictable.

Think about how our town centres will look in a world where no car parks are necessary. Nowadays, car parks need to be close to the places we need to get to such as workplaces, out of town shopping areas and town centres however in a world of automated transport, car parks could be anywhere, perhaps miles outside of the areas we needed to get to in the first place and can also store vehicles with far greater density since the whole system will be controlled by the system.

The most significant difference however is probably that in a world of automated transport, fewer people will need to own cars at all, relying instead on fleets of shared vehicles.

It certainly is strange to think of our great grandchildren marvelling at the 2009 KIA C’eed in a museum and looking with wonder at the old pictures of what used to be the M25 whilst listening to the Road to Hell by Chris Rea. They will probably wonder how we ever managed to cope with being trusted with a couple of tons of fuel injected steel.

What is a Yagi Antenna?

Ask your average person what a Yagi antenna is and they will probably look at you with a puzzled expression. The fact is however that everybody in the UK has probably seen a Yagi antenna and in all likelihood used one at some point.

Example of a Yagi TV aerial.
The ubiquitous TV antenna.

The Yagi antenna was invented by two Japanese researchers in 1926, namely Hidetsugu Yagi and Shintaro Uda.
It is more correctly called the Yagi-Uda antenna however Mr Uda seems to have slipped off the credits somewhat.
It is an example of a subtype of antenna known as the “beam antenna” but having established that its on almost every roof in the UK, why does it interest us at Rustyice Solutions?

In recent years, telecommunications has gone through a revolution with mobile communications becoming the greatest driving force behind this. Whether you like it or not all mobile communication and by definition all radio communication requires an antenna for reception and transmission of the signal. This antenna has largely become hidden from the view of the consumer with form and function of equipments dictating that an antenna can not be visible from the outside in most equipments but they are still there and play a fundamental part in everything that we do in the mobile communications world. So what does the ugly old rooftop TV antenna have to do with todays sleek 21st century devices you may ask?

‘Quite a lot’ is the answer. First, lets look at the technicals of the Yagi antenna itself.

Yagi with folded dipole driven element.

The Yagi antenna is usually made up of a single driven (dipole) elelment and a reflector along with a number of parasitic elements whose size and spacing is determined by the frequencies which one wishes to receive or transmit. The size of the dipole is usually half of the wavelength (?) of the centre frequency or, if a folded dipole is used, the total length of the conductor is equal to almost 1 x ?. It is directional along the axis perpendicular to the dipole in the plane of the elements, from the reflector toward the driven (dipole) element and the parasitic elements which are also known as directors. Typical spacings between elements vary from about 1/10 to 1/4 of a wavelength, depending on the specific design and performance requirements. The lengths of the directors are smaller than that of the driven element, which is smaller than that of the reflector(s) according to an elaborate design procedure. These elements are usually parallel in one plane, supported on a single crossbar known as a boom.

Laptop USB Yagi antenna

Many of the higher end wireless networking manufacturers use emulated yagi antennas in their products today however we are sure you will agree that the coolest gizmo to get yourself a wifi signal where everybody else just simply can and will not be able to connect is this example of antenna technology at its finest over there on the left. In all, we believe, a perfect example of how technology might surge ahead at great speed every day but there really is no escape from good old fashioned antenna theory when you want to get yourself connected on the move.

At Rustyice Solutions, we have many shared years of experience in the field of HF, VHF, UHF and even SHF radio communications. If you or your business needs help getting connected on the fringes of reasonable reception via off the shelf products why not give us a call. We are sure we will be able to bring our considerable experience to bear in getting you connected. Of course you could always go for the item below which, it is said can connect to a wifi network at a range of 10 miles but youre as likely to get the jail as get connected so maybe you should just leave it to us.

The (Day of the Jackal) YAGI sniper rifle

 

Could ants power Web3.0 to new heights? OSPF v’s ANTS

One of our engineers having recently completed their latest M.Eng block on the subject of “Natural and Artificial Intelligence“, became aware of advances made in the recent decade towards a new paradigm of network traffic engineering that was being researched. This new model turns its back on traditional destination based solutions, (OSPF, EIGRP, MPLS) to the combinatorial problem of decision making in network routing  favouring instead a constructive greedy heuristic which uses stochastic combinatorial optimisation. Put in more accessible terms, it leverages the emergent ability of sytems comprised of quite basic autonomous elements working together, to perform a variety of complicated tasks with great reliability and consistency.

In 1986, the computer scientist Craig Reynolds set out to investigate this phenomenon through computer simulation. The mystery and beauty of a flock or swarm is perhaps best described in the opening words of his classic 1986 paper on the subject:

The motion of a flock of birds is one of nature’s delights. Flocks and related synchronized group behaviors such as schools of fish or herds of land animals are both beautiful to watch and intriguing to contemplate. A flock … is made up of discrete birds yet overall motion seems fluid; it is simple in concept yet is so visually complex, it seems randomly arrayed and yet is magnificently synchronized. Perhaps most puzzling is the strong impression of intentional, centralized control. Yet all evidence dicates that flock motion must be merely the aggregate result of the actions of individual animals, each acting solely on the basis of its own local perception of the world.

An analogy with the way ant colonies function has suggested that the emergent behaviour of ant colonies to reliably and consistently optimise paths could be leveraged to enhance the way that the combinatorial optimisation problem of complex network path selection is solved.

The fundamental difference between the modelling of a complex telecommunications network and more commonplace problems of combinatorial optimisation such as the travelling salesman problem is that of the dynamic nature of the state at any given moment of a network such as the internet. For example, in the TSP the towns, the routes between them and the associated distances don’t change. However, network routing is a dynamic problem. It is dynamic in space, because the shape of the network – its topology – may change: switches and nodes may break down and new ones may come on line. But the problem is also dynamic in time, and quite unpredictably so. The amount of network traffic will vary constantly: some switches may become overloaded, there may be local bursts of activity that make parts of the network very slow, and so on. So network routing is a very difficult problem of dynamic optimisation. Finding fast, efficent and intelligent routing algorithms is a major headache for telcommunications engineers.

So how you may ask, could ants help here? Individual ants are behaviourally very unsophisticated insects. They have a very limited memory and exhibit individual behaviour that appears to have a large random component. Acting as a collective however, ants manage to perform a variety of complicated tasks with great reliability and consistency, for example, finding the shortest routes from their nest to a food source.

These behaviours emerge from the interactions between large numbers of individual ants and their environment. In many cases, the principle of stigmergy is used. Stigmergy is a form of indirect communication through the environment. Like other insects, ants typically produce specific actions in response to specific local environmental stimuli, rather than as part of the execution of some central plan. If an ant’s action changes the local environment in a way that affects one of these specific stimuli, this will influence the subsequent actions of ants at that location. The environmental change may take either of two distinct forms. In the first, the physical characteristics may be changed as a result of carrying out some task-related action, such as digging a hole, or adding a ball of mud to a growing structure. The subsequent perception of the changed environment may cause the next ant to enlarge the hole, or deposit its ball of mud on top of the previous ball. In this type of stigmergy, the cumulative effects of these local task-related changes can guide the growth of a complex structure. This type of influence has been called sematectonic. In the second form, the environment is changed by depositing something which makes no direct contribution to the task, but is used solely to influence subsequent behaviour which is task related. This sign-based stigmergy has been highly developed by ants and other exclusively social insects, which use a variety of highly specific volatile hormones, or pheromones, to provide a sophisticated signalling system. It is primarily this second mechanism of sign based sigmergy that has been successfully simulated with computer models and applied as a model to a system of network traffic engineering.

In the traditional network model, packets move around the network completely deterministically. A packet arriving at a given node is routed by the device which simply consults the routing table and takes the optimum path based on its destination. There is no element of probability as the values in the routing table represent not probabilities, but the relative desirability of moving to other nodes.

In the ant colony optimisation model, virtual ants also move around the network, their task being to constantly adjust the routing tables according to the latest information about network conditions. For an ant, the values in the table are probabilities that their next move will be to a certain node.The progress of an ant around the network is governed by the following informal rules:

  • Ants start at random nodes.
  • They move around the network from node to node, using the routing table at each node as a guide to which link to cross next.
  • As it explores, an ant ages, the age of each individual being related to the length of time elapsed since it set out from its source. However, an ant that finds itself at a congested node is delayed, and thus made to age faster than ants moving through less choked areas.
  • As an ant crosses a link between two nodes, it deposits pheromone however, it leaves it not on the link itself, but on the entry for that link in the routing table of the node it left. Other ‘pheromone’ values in that column of the nodes routing table are decreased, in a process analogous to pheromone decay.
  • When an ant reaches its final destination it is presumed to have died and is deleted from the system.R.I.P.

Testing the ant colony optimisation system, and measuring its performance against that of a number of other well-known routing techniques produced good results and the system outperformed all of the established mechanisms however there are potential problems of the kind that constantly plague all dynamic optimisation algorithms. The most significant problem is that, after a long period of stability and equilibrium, the ants will have become locked into their accustomed routes. They become unable to break out of these patterns to explore new routes capable of meeting new conditions which could exist if a sudden change to the networks conditions were to take place. This can be mitigated however in the same way that evolutionary computation introduces mutation to fully explore new possibilities by means of the introduction of an element of purely random behaviour to the ant.

‘Ant net’ routing has been tested on models of US and Japanese communications networks, using a variety of different possible traffic patterns. The algorithm worked at least as well as, and in some cases much better than, four of the best-performing conventional routing algorithms. Its results were even comparable to those of an idealised ‘daemon’ algorithm, with instantaneous and complete knowledge of the current state of the network.

It would seem we have not heard the last of these routing antics…. (sorry, couldnt resist).